Location Selection of Charging Stations based on Improved Evolutionary Algorithms

Authors

  • Kuo Li Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd. Guangzhou City, Guangdong Province, China
  • Yi Wang Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd. Guangzhou City, Guangdong Province, China
  • Haiyi Pan Guangzhou Power Supply Bureau of Guangdong Power Grid Co. Ltd. Guangzhou City, Guangdong Province, China

Abstract

Improving the efficiency of the charging network is key to the development of electric vehicles, and is also an important process in the commercialization and industrialization of electric vehicles. Ensuring the convenient layout of charging stations is important in terms of infrastructure investment, operational safety and the quality of charging stations. If the location and capacity of charging stations are not appropriate, this may affect the travel convenience of users and the planning and layout of the urban transportation network, thus affecting the wide application of electric vehicles. It may also lead to a significant increase in power consumption and a significant drop in the voltage of some nodes. The location and capacity of charging
stations must be optimal for the convenience of electric vehicle users and to improve the operational benefits of charging stations. By comprehensively considering the various influencing factors of charging stations, three important indicators affecting the planning of charging stations, namely economy, average utilization rate of charging stations and charging convenience of users are constructed. The multi-objective planning model of electric vehicle charging stations was established and the designed double-layer coding method was used to optimize the evolutionary algorithm to solve the problem.
Finally, an example is given to illustrate the effectiveness of the proposed model and the evolutionary algorithm for design optimization. An improved evolutionary algorithm is used to analyze a city example.

Keywords: Charging station, Location selection, Improved evolutionary algorithms

Cite As

K. Li, Y. Wang, H. Pan, "Location Selection of Charging Stations based on Improved Evolutionary Algorithms",
vol. 30 no. 4, pp. 285-292, 2022.



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Published

2022-07-01

Issue

Vol. 30 No. 4 (2022): International Journal of Engineering Intelligent Systems

Section

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